286 lines
12 KiB
Python
286 lines
12 KiB
Python
import logging
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import asyncio
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from typing import Union, Tuple, Dict
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from aiohttp.client import ClientSession
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from bs4 import BeautifulSoup
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from bs4.element import Tag, ResultSet
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from webutils import in_async_session, gather_in_batches
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from .constants import (HTML_PARSER, BASE_URL, END_DATE, BS, IS, CF, FIN_STMT_URL_SUFFIX, DEFAULT_CONCURRENT_BATCH_SIZE,
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INDENT_MAP)
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log = logging.getLogger(__name__)
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# First element in each Tuple is an integer indicating the row indent
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HeaderData = Tuple[int, str, str, str, str, str]
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RowData = Tuple[int, float, float, float, float, float]
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# The resulting dictionary's keys correspond to the name of the item (row) in the financial statement.
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# The first value is a tuple of the end dates of the reporting periods as strings (see above).
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# The other values are the actual data tuples containing the financial figures.
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ResultDict = dict[str, Union[HeaderData, RowData]]
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@in_async_session
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async def soup_from_url(url: str, session: ClientSession = None) -> BeautifulSoup:
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"""
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Requests a web page and turns the response text into BeautifulSoup.
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Args:
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url:
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The GET request is sent to this URL
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session (optional):
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If passed an `aiohttp.ClientSession` object, it will be used to perform the request.
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Otherwise a new session is created and automatically closed after the request (see `@in_async_session`).
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Returns:
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The parsed html response text as BeautifulSoup
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"""
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async with session.get(url) as response:
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html = await response.text()
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return BeautifulSoup(html, HTML_PARSER)
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def get_row_indent(tr: Tag) -> int:
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"""
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Determines the visual indent of a table row.
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Some positions in a financial statement have sub-positions below them indicated by indentation of the text in the
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position name's cell.
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Args:
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tr: The table row element
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Returns:
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Each indentation level corresponds to an integer. 0 = no indentation, 1 = small, 2 = medium, 3 = large
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"""
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try:
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classes = tr.div.attrs['class']
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except KeyError:
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return 0
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for class_name, indent in INDENT_MAP.items():
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if class_name in classes:
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return indent
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return 0
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def extract_end_dates(soup: BeautifulSoup) -> HeaderData:
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"""
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Finds and returns the end dates of the reporting periods as strings (either years or quarters) from the page of a
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financial statement.
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Args:
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soup: The parsed page containing the financial statement
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Returns:
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A 6-tuple, the first element being the indent (in this case 0) and the rest being the actual end dates.
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"""
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tr = soup.find('div', attrs={'class': 'financials'}).thead.tr
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ths = tr.find_all('th')
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return (0, ) + tuple(str(th.string).strip() for th in ths[1:-1])
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def get_all_table_rows(soup: BeautifulSoup) -> ResultSet:
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"""
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Returns the table rows containing the data of interest.
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Args:
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soup: The parsed page containing the financial statement
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Returns:
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All table rows containing data from the financial statement
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"""
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return soup.find('div', attrs={'class': 'financials'}).tbody.find_all('tr')
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def extract_row_data(tr: Tag) -> Tuple[str, RowData]:
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"""
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Returns the name of the item displayed in the table row (of a financial statement)
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as well as the position's indent and a figure for each reporting period.
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Args:
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tr: A table row containing data from a financial statement
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Returns:
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2-tuple where the 1st element is the position's name and the second is a 6-tuple, of which the first element is
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the indent and the rest are the actual figures.
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"""
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item_name = str(tr.td.div.string).strip()
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data_div = tr.find_all('td')[-1].div.div
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values_str: str = data_div.attrs['data-chart-data']
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values = tuple(float(s if s != '' else 0) for s in values_str.split(','))
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return item_name, (get_row_indent(tr), ) + values
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def extract_all_data(soup: BeautifulSoup) -> ResultDict:
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"""
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Extracts financials from the page, which can contain either a balance sheet, income statement or cash flow
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statement.
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Args:
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soup: The parsed page containing a financial statement
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Returns:
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Custom result dictionary (see `ResultDict`)
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"""
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output = {END_DATE: extract_end_dates(soup)}
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for row in get_all_table_rows(soup):
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row_data = extract_row_data(row)
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output[row_data[0]] = row_data[1]
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return output
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@in_async_session
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async def get_single_company_fin_stmt(statement: str, ticker_symbol: str, quarterly: bool = False,
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session: ClientSession = None) -> ResultDict:
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"""
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Returns data from the specified financial statement of the specified company.
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Args:
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statement:
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Must be one of the strings defined in the constants `BS`, `IS`, `CF`
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ticker_symbol:
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The company's stock ticker symbol
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quarterly (optional):
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If true the financial data of the last five quarters is scraped; otherwise (default) the last five years.
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session (optional):
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See `soup_from_url`
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Returns:
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Custom result dictionary (see `ResultDict`)
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"""
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log.info(f"Scraping {statement} for {ticker_symbol}")
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url = f'{BASE_URL}/{ticker_symbol}/financials{FIN_STMT_URL_SUFFIX[statement]}'
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if quarterly:
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url += '/quarter'
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soup = await soup_from_url(url, session)
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return extract_all_data(soup)
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@in_async_session
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async def get_multi_companies_fin_stmt(statement: str, *ticker_symbols: str, quarterly: bool = False,
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concurrent_batch_size: int = DEFAULT_CONCURRENT_BATCH_SIZE,
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session: ClientSession = None) -> Union[ResultDict, Dict[str, ResultDict]]:
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"""
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Returns data from the specified financial statement of the specified companies.
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Args:
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statement:
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See `get_single_company_fin_stmt`
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ticker_symbols:
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Arbitrary number of companies' stock ticker symbols
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quarterly (optional):
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See `get_single_company_fin_stmt`
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concurrent_batch_size (optional):
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If multiple ticker symbols are passed, the company financials can be scraped concurrently.
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This argument determines how many companies are scraped concurrently.
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By default, they are scraped sequentially (i.e. a batch size of 1).
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session (optional):
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See `get_single_company_fin_stmt`
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Returns:
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If only one ticker symbol is passed, the `ResultDict` for that financial statement is returned. If multiple
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symbols are passed, a dictionary is returned, where the keys are the symbols and the values are the
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corresponding `ResultDict`s.
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"""
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if len(ticker_symbols) == 1:
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return await get_single_company_fin_stmt(statement, ticker_symbols[0], quarterly, session)
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coroutines = (get_single_company_fin_stmt(statement, symbol, quarterly, session) for symbol in ticker_symbols)
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result_list = await gather_in_batches(concurrent_batch_size, *coroutines)
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return {symbol: data for symbol, data in zip(ticker_symbols, result_list)}
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@in_async_session
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async def get_balance_sheet(*ticker_symbols: str, quarterly: bool = False,
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concurrent_batch_size: int = DEFAULT_CONCURRENT_BATCH_SIZE,
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session: ClientSession = None) -> Union[ResultDict, Dict[str, ResultDict]]:
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"""
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Returns data from the balance sheet of the specified companies.
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Convenience function around `get_multi_companies_fin_stmt`
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"""
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return await get_multi_companies_fin_stmt(BS, *ticker_symbols,
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quarterly=quarterly, concurrent_batch_size=concurrent_batch_size,
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session=session)
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@in_async_session
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async def get_income_statement(*ticker_symbols: str, quarterly: bool = False,
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concurrent_batch_size: int = DEFAULT_CONCURRENT_BATCH_SIZE,
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session: ClientSession = None) -> Union[ResultDict, Dict[str, ResultDict]]:
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"""
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Returns data from the income statement of the specified companies.
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Convenience function around `get_multi_companies_fin_stmt`
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"""
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return await get_multi_companies_fin_stmt(IS, *ticker_symbols,
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quarterly=quarterly, concurrent_batch_size=concurrent_batch_size,
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session=session)
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@in_async_session
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async def get_cash_flow_statement(*ticker_symbols: str, quarterly: bool = False,
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concurrent_batch_size: int = DEFAULT_CONCURRENT_BATCH_SIZE,
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session: ClientSession = None) -> Union[ResultDict, Dict[str, ResultDict]]:
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"""
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Returns data from the cash flow statement of the specified companies.
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Convenience function around `get_multi_companies_fin_stmt`
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"""
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return await get_multi_companies_fin_stmt(CF, *ticker_symbols,
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quarterly=quarterly, concurrent_batch_size=concurrent_batch_size,
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session=session)
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@in_async_session
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async def get_single_company_all_financials(ticker_symbol: str, quarterly: bool = False,
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session: ClientSession = None) -> Dict[str, ResultDict]:
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"""
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Returns data from all financial statements of the specified company.
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Concurrently calls `get_single_company_fin_stmt` three times.
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Args:
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ticker_symbol:
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The company's stock ticker symbol
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quarterly (optional):
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See `get_single_company_fin_stmt`
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session (optional):
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See `get_single_company_fin_stmt`
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Returns:
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A dictionary where the keys are the three different statement names and the values are the
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corresponding `ResultDict`s
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"""
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coroutines = (get_single_company_fin_stmt(stmt, ticker_symbol, quarterly, session) for stmt in (BS, IS, CF))
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results = await asyncio.gather(*coroutines)
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return {stmt: data for stmt, data in zip((BS, IS, CF), results)}
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@in_async_session
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async def get_all_financials(*ticker_symbols: str, quarterly: bool = False,
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concurrent_batch_size: int = DEFAULT_CONCURRENT_BATCH_SIZE,
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session: ClientSession = None) -> Union[Dict[str, ResultDict],
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Dict[str, Dict[str, ResultDict]]]:
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"""
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Returns all fundamentals (balance sheet, income statement and cash flow statement) of the specified companies.
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Args:
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ticker_symbols:
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Arbitrary number of companies' stock ticker symbols
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quarterly (optional):
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See `get_single_company_all_financials`
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concurrent_batch_size (optional):
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If multiple ticker symbols are passed, the company financials can be scraped concurrently.
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This argument determines how many companies are scraped concurrently.
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By default, they are scraped sequentially (i.e. a batch size of 1).
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session (optional):
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See `get_single_company_all_financials`
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Returns:
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If only one ticker symbol is passed, the output of `get_single_company_all_financials` is returned. If multiple
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symbols are passed, a dictionary is returned, where the keys are the symbols and the values are the
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corresponding outputs of `get_single_company_all_financials`.
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"""
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if len(ticker_symbols) == 1:
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return await get_single_company_all_financials(ticker_symbols[0], quarterly, session)
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coroutines = (get_single_company_all_financials(symbol, quarterly, session) for symbol in ticker_symbols)
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result_list = await gather_in_batches(concurrent_batch_size, *coroutines)
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return {symbol: data for symbol, data in zip(ticker_symbols, result_list)}
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